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I hope you’re doing well! I’m currently working with the MAPPO implementation in your repository and have a question regarding GPU configuration for optimal training performance.
Current Setup: I have an environment with an average response time of about 10 seconds. I’m trying to decide between using one high-performance GPU or multiple low-performance GPUs for training.
Question: Based on your experience with this implementation, which option would you recommend? Would one high-performance GPU provide better performance given the response time, or could multiple low-performance GPUs offer any advantages in this scenario?
Additional Context: I'm also interested in how parallelizing the environment might impact the decision and the overall training process.
Thank you for your assistance!
Best regards,
The text was updated successfully, but these errors were encountered:
【Since updating the vectorized environment and multiple GPUs, as of October 12, 2024, I haven't figured out how to incorporate the MADDPG, MAPPO, and QMIX algorithms into the ElegantRL library】
Hi
I hope you’re doing well! I’m currently working with the MAPPO implementation in your repository and have a question regarding GPU configuration for optimal training performance.
Current Setup: I have an environment with an average response time of about 10 seconds. I’m trying to decide between using one high-performance GPU or multiple low-performance GPUs for training.
Question: Based on your experience with this implementation, which option would you recommend? Would one high-performance GPU provide better performance given the response time, or could multiple low-performance GPUs offer any advantages in this scenario?
Additional Context: I'm also interested in how parallelizing the environment might impact the decision and the overall training process.
Thank you for your assistance!
Best regards,
The text was updated successfully, but these errors were encountered: